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Advances in Meteorology
Volume 2014, Article ID 474876, 10 pages
http://dx.doi.org/10.1155/2014/474876
Research Article

Comparison of Satellite and Ground-Based Phenology in China’s Temperate Monsoon Area

1Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, A 11 Datun Road, Chaoyang District, Beijing 100101, China
2University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China

Received 12 February 2014; Revised 20 March 2014; Accepted 20 March 2014; Published 24 April 2014

Academic Editor: Dong Jiang

Copyright © 2014 Huanjiong Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Continuous satellite datasets are widely used in tracking vegetation responses to climate variability. Start of season (SOS), for example, can be derived using a number of methods from the time series of satellite reflectance data; however, various methods often produce different SOS measures which limit the application of satellite data in phenological studies. Therefore, we employed five methods to estimate SOS from the Advanced Very High Resolution Radiometer (AVHRR)/normalized difference vegetation index (NDVI) dataset. Subsequently, we compared the SOS with the ground-based first leaf date (FLD) of 12 deciduous broadleaved plant species at 12 sites of the Chinese Phenological Observation Network (CPON). The results show that the latitudinal patterns of five satellite-derived SOS measures are similar to each other but different from the pattern of ground phenology. For individual methods, the variability of SOS time series is significantly different from ground phenology except for HANTS, Polyfit, and Midpoint methods. The SOS calculated using the Midpoint method showed significant correlations with ground phenophases most frequently (in 47.1% of cases). Using the SOS derived from the Midpoint method, significantly earlier trends in SOS were detected in 50.7% of the natural vegetation area from 1982 to 2006.